class_docstr: The MissingValues Bar visualizer creates a bar graph that lists the total
  count of missing values for each selected feature column.
  
  When y targets are supplied to fit, the output is a stacked bar chart where
  each color corresponds to the total NaNs for the feature in that column.
  
  Parameters
  ----------
  alpha : float, default: 0.5
      A value for bending elments with the background.
  
  marker : matplotlib marker, default: |
      The marker used for each element coordinate in the plot
  
  color : string, default: black
      The color for drawing the bar chart when the y targets are not passed to
      fit.
  
  colors : list, default: None
      The color palette for drawing a stack bar chart when the y targets
      are passed to fit.
  
  classes : list, default: None
      A list of class names for the legend.
      If classes is None and a y value is passed to fit then the classes
      are selected from the target vector.
  
  kwargs : dict
      Keyword arguments that are passed to the base class and may influence
      the visualization as defined in other Visualizers.
  
  Attributes
  ----------
  features_ : np.array
      The feature labels ranked according to their importance
  
  classes_ : np.array
      The class labels for each of the target values
  
  Examples
  --------
  
  >>> from yellowbrick.contrib.missing import MissingValuesBar
  >>> visualizer = MissingValuesBar()
  >>> visualizer.fit(X, y=y)
  >>> visualizer.show()
docstr: Called from the fit method, this method generated a horizontal bar plot.
  
  If y is none, then draws a simple horizontal bar chart.
  If y is not none, then draws a stacked horizontal bar chart for each nan count per
  target values.
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code: def draw(self, X, y, **kwargs):
      """Called from the fit method, this method generated a horizontal bar plot.
  
      If y is none, then draws a simple horizontal bar chart.
      If y is not none, then draws a stacked horizontal bar chart for each nan count per
      target values.
      """
      nan_col_counts = self.get_nan_col_counts()
  
      # the x locations for the groups
      self.ind = np.arange(len(self.features_))
  
      if y is None:
          self.ax.barh(
              self.ind - self.width / 2,
              nan_col_counts,
              self.width,
              color=self.color,
              label=None,
          )
      else:
          self.draw_stacked_bar(nan_col_counts)
  
file_path: yellowbrick/yellowbrick/contrib/missing/bar.py
imports: import numpy
  from yellowbrick.style.palettes import color_palette
  from .base import MissingDataVisualizer
label_desc: Use image node_id 3 for calling the MissingValuesBar obj's underlying member method code with example usage: obj.draw(X, y) without return types